By Topic

Clusterwise data mining within a fuzzy querying interface

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
Kacprzyk, J. ; Syst. Res. Inst., Polish Acad. of Sci., Warsaw, Poland ; Owsinski, J.W. ; Zadrozny, S.

This paper, is a further development of a combined fuzzy querying and data mining paradigm. The point of departure is the FQUERY for Access. Its earlier version offered the generation of fuzzy association rules within the fuzzy querying interface. We report on extensions to a wider range of available data mining tools, mainly from cluster analysis,and more specifically, a clustering algorithm by Owsinski and Zadrozny. The data to be clustered is first fuzzified using a dictionary of linguistic terms. Additionally, the resulting clusters are helpful in running other data mining tools, notably the generation of association rules

Published in:

Fuzzy Systems, 2001. The 10th IEEE International Conference on  (Volume:3 )

Date of Conference:

2001